Method for identifying an unknown fingerprint by generating a numeric representation through interleaving digits

ABSTRACT

A method for searching a database comprising data related to a plurality of fingerprints. In step  301 , two or more feature points in an image of an unknown fingerprint are identified. A plurality of properties are generated in step  302 . The plurality of properties are based on the two or more feature points. In step  303 , a number comprising a plurality of digits, e.g. binary digits, is assigned to each of the plurality of properties. In a subsequent step, step  304 , a numeric representation of said fingerprint is generated based on the assigned numbers. The numeric representation is generated by interleaving the plurality of digits, such that the digits of the numeric representation are arranged in an interleaved or intertwined manner within the numeric representation. In step  305 , the numeric representation is used as a search argument when searching the database. The invention also relates to an apparatus and computer program product.

TECHNICAL FIELD

The present invention relates in general to the field of fingerprintmatching. More particularly, the present invention relates to a method,an apparatus, and a computer program product for searching a databasecomprising data related to a plurality of fingerprints.

DESCRIPTION OF RELATED ART

Prior art fingerprint identification apparatuses and methods identify aperson using the fingerprint of the person as an image that is read byan image sensor or the like. The image sensor reads the fingerprint ofthe person to be identified, and stores an image of the readfingerprint. The image may be examined by an algorithm foridentification purpose. A matching degree may be checked between thefingerprint image and a fingerprint image previously registered in adatabase. This may be accomplished by comparing the fingerprint imagewith a great number of fingerprint images stored in the database. If thematching degree is equal to or more than a threshold value, then theidentity of the person is authenticated. A pattern matching method maybe used to calculate the matching degree between the two fingerprintimages.

In the prior art, a linear search of the entire database may beperformed during the fingerprint matching. Using this approach, a fullsearch of a database potentially involving a million or more comparisonsmay be required. In general, this reduces the speed in the fingerprintmatching process.

There are previously known methods, such as e.g. the HenryClassification System, to classify a fingerprint into main groupsdepending on the structure of the fingerprint. However, it is in generaldifficult to make such classifications without manual intervention in asecure way.

Furthermore, a problem when trying to find an unknown fingerprint in adatabase of fingerprints is that fingerprints taken from the same fingerat different times are almost never the same. The variation in the printmay e.g. depend on, but is not limited to:

-   -   finger plasticity, e.g. the fingerprint is not the same if the        finger is pressed hard against the surface compared to the        fingerprint when the finger is only slightly pressed against the        surface;    -   the fingerprint is distorted due to damp, dirt, moisture etc. on        the surface or on the finger;    -   the size of the contact area between the finger and the surface;    -   the rotation angle of the finger.

Consequently, it may be advantageous to search for not only identicalfingerprint patterns, but also similar or “look-a-like” patterns, whensearching the database during the fingerprint matching. However, usingthe above-mentioned linear search approach when searching for similar or“look-a-like” patterns in the database generally reduces the speedsubstantially.

Hence, an improved method, apparatus and computer program product withinfingerprint searching would be advantageous, allowing for increasedspeed when searching a database comprising data related to a pluralityof fingerprints to find a match.

SUMMARY OF THE INVENTION

Accordingly, the present invention preferably seeks to mitigate,alleviate or eliminate one or more of the above-identified deficienciesin the art and disadvantages singly or in any combination.

According to a first aspect of the invention, a method for searching adatabase comprising data related to a plurality of fingerprints isprovided. The method comprises identifying at least two feature pointsin an image of an unknown fingerprint; generating a plurality ofproperties based on the at least two feature points; assigning a numbercomprising a plurality of digits to each of the plurality of properties;generating a numeric representation of said fingerprint based on theassigned numbers; and using the numeric representation as a searchargument when searching the database; wherein the numeric representationis generated by at least partly interleaving said plurality of digits.

The interleaving may comprise interleaving the plurality of digits suchthat the digits of the numeric representation are arranged in aninterleaved or intertwined manner.

The assigning may comprise assigning a number comprising a plurality ofbits to each of the plurality of properties.

The interleaving may comprise interleaving the most significant bits ofsaid plurality of bits.

The interleaving may comprise interleaving all the bits of saidplurality of bits.

The interleaving may comprise bitwise interleaving of the plurality ofbits.

The interleaving may comprise arranging the plurality of bits in orderof significance, from most significant bits to least significant bitswithin the numeric representation.

In an embodiment, the assigning may comprise assigning a respectivebinary number a₃ a₂ a₁ a₀, b₃ b₂ b₁ b₀, c₃ c₂ c₁ c₀, d₃ d₂ d₁ d₀ . . .N₃ N₂ N₁ N₀ to each of the plurality of properties, and the generatingmay comprise generating the numeric representation by arranging theplurality of bits in the following order: N₃ . . . d₃ c₃ b₃ a₃ N₂ . . .d₂ c₂ b₂ a₂ N₁ . . . d₁ c₁ b₁ a₁ N₀ . . . d₀ c₀ b₀ a₀.

In another embodiment, the assigning may comprise assigning a respectivebinary number a₃ a₂ a₁ a₀, b₃ b₂ b₁ b₀, c₃ c₂ c₁ c₀, d₃ d₂ d₁ d₀ . . .N₃ N₂ N₁ N₀ to each of the plurality of properties, and the generatingmay comprise generating the numeric representation by arranging theplurality of bits in the following order: a₃ b₃ c₃ d₃ . . . N₃ a₂ b₂ c₂d₂ . . . N₂ a₁ b₁ c₁ d₁ . . . a₀ b₀ c₀ d₀ . . . N₀.

In still another embodiment, the assigning may comprise assigning arespective binary number a₇ a₆ a₅ a₄ a₃ a₂ a₁ a₀, b₇ b₆ b₅ b₄ b₃ b₂ b₁b₀, c₇ c₆ c₅ c₄ c₃ c₂ c₁ c₀ d₇ d₆ d₅ d₄ d₃ d₂ d₁ d₀ . . . N₇ N₆ N₅ N₄ N₃N₂ N₁ N₀ to each of the plurality of properties, and the generating maycomprise generating the numeric representation by arranging theplurality of bits in the following order: N₇ . . . d₇ c₇ b₇ a₇ N₆ . . .d₆ c₆ b₆ a₆ N₅ . . . d₅ c₅ b₅ a₅ N₄ . . . d₄ c₄ b₄ a₄ N₃ . . . d₃ c₃ b₃a₃ N₂ . . . d₂ c₂ b₂ a₂ N₁ . . . d₁ c₁ b₁ a₁ N₀ . . . d₀ c₀ b₀ a₀.

In yet another embodiment, the assigning may comprise assigning arespective binary number a₇ a₆ a₅ a₄ a₃ a₂ a₁ a₀, b₇ b₆ b₅ b₄ b₃ b₂ b₁b₀, c₇ c₆ c₅ c₄ c₃ c₂ c₁ c₀ d₇ d₆ d₅ d₄ d₃ d₂ d₁ d₀ . . . N₇ N₆ N₅ N₄ N₃N₂ N₁ N₀ to each of the plurality of properties, and the generating maycomprise generating the numeric representation by arranging theplurality of bits in the following order: a₇ b₇ c₇ d₇ . . . N₇ a₆ b₆ c₆d₆ . . . N₆ a₅ b₅ c₅ d₅ N₅ a₄ b₄ c₉ d₄ . . . N₄ a₃ b₃ c₃ d₃ . . . N₃ a₂b₂ c₂ d₂ N₂ a₁ b₁ c₁ d₁ . . . N₁ a₀ b₀ c₀ d₀ . . . N₀.

In another embodiment, the assigning may comprise assigning a respectivebinary number a₇ a₆ a₅ a₄ a₃ a₂ a₁ a₀, b₇ b₆ b₅ b₄ b₃ b₂ b₁ b₀, c₇ c₆ c₅c₄ c₃ c₂ c₁ c₀ d₇ d₆ d₅ d₄ d₃ d₂ d₁ d₀ . . . N₇ N₆ N₅ N₄ N₃ N₂ N₁ N₀ toeach of the plurality of properties, and the generating may comprisegenerating the numeric representation by arranging the plurality of bitsin the following order: a₇ a₆ a₅ a₄ a₃ a₂ a₁ a₀ a₇ b₇ c₇ d₇ . . . N₇ b₆c₆ d₆ . . . N₆ b₅ c₅ d₅ . . . N₅ b₄ c₄ d₄ . . . N₄ b₃ c₃ d₃ . . . N₃ b₂c₂ d₂ . . . N₂ b₁ c₁ d₁ . . . N₁ b₀ c₀ d₀ . . . N₀.

The method may also comprise masking away at least some of the leastsignificant bits of said plurality of bits.

The method may further comprise, after the step of assigning, grouping aplurality of properties into a plurality of subsets of properties. Then,the generating may comprise generating a plurality of numericrepresentations of said fingerprint based on said subsets of properties,wherein each of the numeric representations may be generated by at leastpartly interleaving said plurality of digits. Furthermore, the using maycomprise using the plurality of numeric representations as searcharguments when searching the database.

According to a second aspect of the invention, there is provided acomputer program product comprising program instructions for causing acomputer system to perform the method according to the first aspect ofthe invention when the program instructions are run on a computer systemhaving computer capabilities. The computer program product may e.g. beembodied on a record medium, stored in a computer memory, embodied in aread-only memory, or carried on an electrical carrier signal.

According to a third aspect of the invention, an apparatus for searchinga database comprising data related to a plurality of fingerprints,comprises: an identification unit adapted to identify at least twofeature points in an image of an unknown fingerprint; a first generationunit adapted to generate a plurality of properties based on the at leasttwo feature points; an assignment unit adapted to assign a numbercomprising a plurality of digits to each of the plurality of properties;a second generation unit adapted to generate a numeric representation ofsaid fingerprint based on the assigned numbers; and a search unitadapted to use the numeric representation as a search argument whensearching the database. The second generation unit is adapted togenerate said numeric representation by at least partly interleavingsaid plurality of digits.

According to a fourth aspect of the invention, there is provided a useof the method, the apparatus or the computer program product accordingto any of the aspects of the invention. The use of the method, theapparatus or the computer program product may e.g. be in a crime sceneinvestigation, a police control, an authentication equipment or apassage system at an airport, industrial park or building, etcetera.

Further embodiments of the invention are defined in the dependentclaims.

BRIEF DESCRIPTION OF THE DRAWINGS

Further objects, features and advantages of the invention will appearfrom the following detailed description of embodiments of the invention,reference being made to the accompanying drawings, in which:

FIG. 1 is a pictorial representation of a fingerprint and the featurepoints therein;

FIG. 2 is a pictorial representation of parametric data thatcharacterize the feature points of the fingerprint in FIG. 1;

FIG. 3 is a flowchart illustrating a method according to an embodimentof the present invention;

FIG. 4A is a table;

FIG. 4B is another table;

FIG. 5 is a block diagram of an apparatus according to an embodiment ofthe present invention; and

FIG. 6 is a block diagram of a computer program product according to anembodiment of the present invention.

DETAILED DESCRIPTION OF EMBODIMENTS

The embodiments described below disclose the best mode and enables aperson ordinary skilled in the art to carry out the invention. Thedifferent features of the embodiments can be combined in other mannersthan described below. The invention may be embodied in many differentforms and should not be construed as limited to the embodiments setforth herein. Rather, these embodiments are provided so that thisdisclosure will be thorough and complete, and will fully convey thescope of the invention to those skilled in the art. The invention isonly limited by the appended patent claims.

An embodiment of the method will be described below. The methodgenerally comprises the following steps: identification of featurepoints; generation of properties; assigning a number; generation of arepresentation; and using the representation when searching a database.Each of the steps will be described below.

Identification of feature points involves identification of two or morefeature points in an image of an unknown fingerprint.

Generation of properties involves generation of a plurality ofproperties based on the two or more feature points.

Assigning a number involves assigning a number comprising a plurality ofdigits, e.g. a plurality of binary digits (bits), to each of theplurality of properties.

Generation of a representation involves generation of a numericrepresentation of said fingerprint based on the assigned numbers. Saidnumeric representation is generated by at least partly interleaving saidplurality of digits. Accordingly, the digits of the numericrepresentation may be arranged in an interleaved or intertwined mannerwithin the numeric representation. Therefore, the generation of thenumeric representation may be referred to as interleaved inclusion ofthe digits of the plurality of digits into a single numericrepresentation.

Using the representation when searching a database involves searching adatabase comprising data related to a plurality of fingerprints by usingthe numeric representation as search argument.

In an embodiment, the method further comprises, after the assigning,grouping a plurality of properties into a plurality of subsets ofproperties. In this embodiment, the generation involves generating aplurality of numeric representations of said fingerprint based on saidsubsets of properties. Furthermore, the using then involves using theplurality of numeric representations as search arguments when searchingsaid database.

It has turned out by experiment that by representing said fingerprint bysaid numeric representation(s) it is possible to find similar-shaped orlook-a-like properties in a database comprising data related to aplurality of fingerprints with improved speed when compared to prior artsolutions. It has turned out that it possible to perform a search in asorted list of said database with a speed improvement. In fact, thespeed may be improved with a speed factor up to and includingapproximately 100 according to some embodiments of the invention.

Fingerprint

FIG. 1 illustrates a representation 100 of a portion of a fingerprint10, such as a human fingerprint. The fingerprint 10 is typicallyrepresented by one or more properties characterizing a collection offeature points, commonly referred to as “minutiae points”, associatedwith the fingerprint 10. The feature points associated with thefingerprint 10 are typically derived from an image of the fingerprint 10using e.g. image processing techniques, all of which may be implementedby embodiments of the invention. Different image processing techniquesfor this purpose are known in the art and may be implemented by thoseordinary skilled in the art.

The feature points of a fingerprint 10 may be determined or derived fromsingularities in the ridge pattern of the fingerprint 10. As isillustrated in FIG. 1, the ridge pattern may comprise singularities suchas, e.g., ridge terminations and ridge bifurcations. Point A is anexample of a ridge termination, whereas points B and C are an example ofa ridge bifurcation. As is illustrated in a representation 200 of FIG.2, each local feature point can be represented by the coordinates (x, y)of the local feature in a reference system common to all of the localfeature points in the given fingerprint image.

During the fingerprint matching process, two or more feature points inthe unknown fingerprint 10 are identified. A plurality of properties arethen subsequently generated, based on the two or more identified featurepoints. Each property of the plurality of properties is in generalunique for the identified feature points and may thus characterize theunknown fingerprint 10 at least in the vicinity of the identifiedfeature points.

Property

There exist many different types of properties, i.e. biometricproperties, all of which may be used or implemented by the embodimentsof the present invention. Hereinbelow, some examples of properties aredescribed so that this disclosure will be thorough and complete forthose skilled in the art to carry out the embodiments of the invention.However, the examples mentioned below are not intended to limit thescope of the invention.

A property may be the distance D associated with a pair of featurepoints. More specifically, the distance D associated with a particularpair of feature points may represent the distance of a line drawnbetween two identified feature points.

A property may be the local direction θ of the ridge pattern atcoordinates (x, y) of each of the identified feature points. Morespecifically, the local direction θ associated with a particular featurepoint may represent the direction of the ridge, or the image gradient atthe particular feature point with respect to a line drawn from theparticular feature point to another feature point. It should beunderstood that the gradient in a certain point (x, y) in general pointsin the direction where there are great changes in the pixel values inthe vicinity of the point, which is typically considered to be acriterion for an edge.

A property may be the angle α of the ridge pattern at coordinates (x, y)of each of the identified feature points. More specifically, the angle αassociated with a particular feature point may represent the anglebetween a first direction of the ridge at the particular feature pointwith respect to a line drawn from the particular feature point toanother feature point and a second direction of the ridge at theparticular feature point with respect to a line drawn from theparticular feature point to still another feature point.

A property may be the ridge count RC associated with a pair of featurepoints. More specifically, the ridge count RC associated with a givenpair of feature points may be the number of ridges crossed by a linedrawn between the corresponding feature points.

A property may be the area A associated with three or more identifiedfeature points.

As one illustrative example, some properties characterizing thefingerprint 10 in the vicinity of the identified feature points A-B-C ofthe unknown fingerprint 10 are shown in FIG. 2. In this example, theproperties include D₁, D₂, D₃, θ₁, θ₂, θ₃, α₁, α₂, α₃ and A. Inaddition, the properties may include the ridge counts RC_(1A-B),RC_(A-C), RC_(B-C) (not shown), where RC_(A-B) represents the number ofridges crossed by a line drawn between feature points A and B, whereRC_(A-C) represents the number of ridges crossed by a line drawn betweenfeature points A and C, and where RC_(B-C) represents the number ofridges crossed by a line drawn between feature points B and C.

Method

FIG. 3 illustrates an embodiment of a method 300 for searching adatabase comprising data related to a plurality of fingerprints. Thedatabase may, e.g., be a large database. A large database in generalcomprises several millions of records, such as e.g. ten million recordsor more.

In a first step, step 301, two or more feature points in an image of anunknown fingerprint 10 are identified. The two or more feature pointsmay be derived or determined from the singularities in ridge patterns inthe unknown fingerprint 10. The step 301 of identifying feature pointsmay include extracting the feature points.

In a next step, step 302, a plurality of properties, i.e. two or moreproperties, are generated based on the two or more feature points thatare identified in the unknown fingerprint 10 in step 301. The step 302of generating the plurality of properties may comprise grouping orcollecting the two or more feature points into one or more subsets (e.g.triplets). Each subset may be associated with two or more featurepoints. For each subset, which may be selected, one or more propertiesthat characterize the selected subset may be generated.

The one or more properties that are generated in step 302 may, e.g., beone or more of the properties described above under the sectionPROPERTY. That is, the one or more properties may be selected from thegroup comprising: a distance between two feature points; a direction ofa ridge at a particular feature point with respect to a line drawn fromthe particular feature point to another feature point; an angle of theridge pattern at the coordinates of a particular feature point; a numberof ridges crossed by a line drawn between the two feature points; and anarea associated with the at least one subset of feature points.

There exist many different implementations for performing the steps301-303, i.e. identifying feature points and/or generating theassociated properties representing the fingerprint 10, all of which maybe used by the embodiments of the present invention. Different methodsfor identifying feature points and/or generating the associatedproperties are known in the art and may be implemented by those skilledin the art. Therefore, it will not be further explained herein.

It may be advantageous to limit the number of properties to beidentified in step 301. To limit the amount of properties, theproperties may be filtered according to certain criteria. Such criteriamay e.g. be, but is not limited to, maximum and/or minimum values of theproperty in question. Accordingly, such criteria may e.g. be maximumand/or minimum values of the distances between the identified featurepoints, maximum and/or minimum values of the area covered by the linesconnecting the identified feature points (if there are three or moreidentified feature points), etc. Various rules for reducing or limitingthe number of properties by filtering using certain criteria can beimplemented by the embodiments of the present invention. Yet anotherrule for limiting the number of properties may be to include only thoseproperties where the difference between image gradients, or ridgedirections, in the feature points, fulfill certain filter criteria.

In step 303, a number is assigned to each property of the plurality ofproperties. The number comprises a plurality of digits. The number may,for example, be a number comprising a plurality of binary digits (bits).The number may e.g. comprise 4 bits (i.e. a nibble), 6 bits, 8 bits(i.e. a byte), 16 bits, 24 bits, 32 bits or even more bits.

Referring now to FIG. 2, in an illustrative example four properties D₁,D₂, α₁ and A_(A-B-C) are generated from the three identified featurepoints A-B-C of the fingerprint 10. In step 303, these four propertiesmay e.g. be assigned the following binary numbers of one byte each a₇ a₆a₅ a₄ a₃ a₂ a₁ a₀, b₇ b₆ b₅ b₄ b₃ b₂ b₁ b₀, c₇ c₆ c₅ c₄ c₃ c₂ c₁ c₀, andd₇ d₆ d₅ d₄ d₃ d₂ d₁ d₀, respectively. That is, D₁ is assigned thenumber a₇ a₆ a₅ a₄ a₃ a₂ a₁ a₀, D₂ is assigned the number b₇ b₆ b₅ b₄ b₃b₂ b₁ b₀ and so forth.

In step 304, a numeric representation of the fingerprint 10 is generatedbased on the assigned numbers. The numeric representation is formed byat least partly interleaving the plurality of digits of the plurality ofproperties. Hence, the numeric representation will represent or at leastbe associated with the plurality of properties. Accordingly, the numericrepresentation may be configured to characterize the fingerprint 10 atleast in the vicinity of the identified two or more feature points.Thus, a single numeric representation can be formed in step 304, whereinat least some of the digits of the numeric representation are arrangedin an interleaved or intertwined manner.

Creating or generating one single numeric representation based on theassigned numbers for the plurality of properties has, inter alia, theadvantage that the derived single numeric representation will in generalget more and more unique the more properties that are included into thesingle numeric representation. In an embodiment, the assigned numbersare formed by a plurality of bits as described hereinabove. Theinterleaving of the plurality of bits may comprise interleaving theplurality of bits such that the numeric representation forms a singlevalue. The single value may be in the form of a bit stream, wherein thebits of the bit stream are arranged in an interleaved or intertwinedmanner. The numeric representation may e.g. be created or generated suchthat all of the bits, or just those bits regarded as significant bits,of the assigned numbers of the respective properties are included in theinterleaved or intertwined manner into the single numericrepresentation.

It should be understood that the number of involved properties in thecombined single numeric representation may be any number greater than 1.Furthermore, it should be understood that grouping of binary bits fromeach property before being interleaved into the single numericrepresentation may be from 1 bit up to the total length of the property(typically, but not limited to, one byte).

Referring again to FIG. 2 and the example above, various examples of thenumeric representation will now be described.

According to an embodiment of the invention, the numeric representationis generated by arranging the binary digits in the following order: d₇c₇ b₇ a₇ d₆ c₆ b₆ a₆ d₅ c₅ b₅ a₅ d₄ c₄ b₄ a₄ d₃ c₃ b₃ a₃ d₂ c₂ b₂ a₂ d₁c₁ b₁ a₁ d₀ c₀ b₀ a₀.

According to another embodiment of the invention, the numericrepresentation is created by arranging the bits in the following order:a₇ b₇ c₇ d₇ a₆ b₆ c₆ d₆ a₅ b₅ c₅ d₅ a₄ b₄ c₄ d₄ a₃ b₃ c₃ d₃ a₂ b₂ c₂ d₂a₁ b₁ c₁ d₁ a₀ b₀ c₀ d₀.

According to some embodiments, the generation or creation of the numericrepresentation comprises interleaving only the most significant bits ofsaid plurality of bits.

In an embodiment, the numeric representation is created by arranging thebits in the following order: a₇ a₆ a₅ a₄ a₃ a₂ a₁ a₀ a₇ b₇ c₇ d₇ b₆ c₆d₆ b₅ c₅ d₅ b₄ c₄ d₄ b₃ c₃ d₃ b₂ c₂ d₂ b₁ c₁ d₁ b₀ c₀ d₀.

In another embodiment, the generation of the numeric representationcomprises interleaving only the two most significant bits of eachproperty according to the following sequence of bits: d₇ c₇ b₇ a₇ d₆ c₆b₆ a₆ d₅ d₄ d₃ d₂ d₁ d₀ c₅ c₄ c₃ c₂ c₁ c₀ b₅ b₄ b₃ b₂ b₁ b₀ a₅ a₄ a₃ a₂a₁ a₀.

In still another embodiment, the generation of the numericrepresentation comprises interleaving only the two or three mostsignificant bits of each property, etc. Due to variations in imagequality of the fingerprint 10, contact pressure etc., it is in generalreasonable to assume that the two least significant bits in eachproperty is insignificant or at least of little significance. This meansthat the 8 bits of the numeric representation can be masked away. In anembodiment, the numeric representation may thus e.g. be generated byarranging the bits in the following order: d₇ c₇ b₇ a₇ d₆ c₆ b₆ a₆ d₅ c₅b₅ a₅ d₄ c₄ b₄ a₄ d₃ c₃ b₃ a₃ d₂ c₂ b₂ a₂.

When creating the numeric representation, it should be understood thatthe aim is to make the numeric representation as unique as possible.Therefore some LSD's in the participating properties may be masked awaysince they may vary due to dirt, moisture etc. The released space mayinstead be used for adding significant bits from one or more propertytypes. Another potential reason for masking away some LSD's in theparticipating properties is that an aim of embodiments of the presentinvention is to search for similar or look-a-like properties. Havingthis in mind, it should be realized that some LSD's in the participatingproperties are not relevant for achieving a good result.

In step 305, the numeric representation is used as a search argumentwhen searching the database comprising data related to a plurality offingerprints. Accordingly, the numbers representing properties in theunknown fingerprint 10 are used as binary search arguments for similaror look-a-like properties that are stored in the database. That is, thesearch for identical or similar fingerprints in step 305 comprisessearching for corresponding properties in a database comprising datarelated to a plurality of fingerprints.

In an embodiment, the method further comprises, after the assigning instep 303, the further step of grouping a plurality of properties into aplurality of subsets of properties. In this embodiment, the step ofgenerating, i.e. step 304, comprises generating a plurality of numericrepresentations of said fingerprint based on said subsets of properties.Furthermore, the step 305 comprises using the plurality of numericrepresentations as search arguments when searching the database.

As one illustrative example, the database comprising data related to aplurality of fingerprints may comprise a global table of numericrepresentations from previously stored fingerprints. Each element in theglobal table may comprise not only the numeric representation of thefingerprint, but also a numeric representation of the identity of theperson from which the fingerprint originates. Said numericrepresentation of the identity, may be called owner's index.

In an embodiment, the search may result in a number of similar numericrepresentations, which may be stored in a temporary table T1. Sortingthe table T1 on the owner's index and by counting the number a certainowner is found, a second table T2 may be created. Table T2 may thuscomprise owner's index and the frequency count of properties for theowner. When sorted on frequency count in decreasing order T2 maycomprise a list with the most likely owner first in the list.

With the aim of identifying the most likely owner found in T2, theowner's index is, in a first step, used to retrieve a fingerprint, orthe representation thereof, for the most likely owner from a database.In a second step, a first plurality of numeric representations of theunknown fingerprint is generated using filter conditions. In a thirdstep, a second plurality of numeric representations of the knownfingerprint retrieved from the database is generated using the same orsimilar filter conditions as for the first plurality. In a fourth step,each numeric representation in the first set is compared to each numericrepresentation in the second plurality. If two representations aresimilar to each other, the representations may create a matching pair.When all representations in the two said pluralities have been compared,a plurality of matching pairs has been created.

In a fifth step, a rotation angle, for each said matching pair, iscalculated. The rotation angle is represented by the angle between oneline through two of the participating feature points in the firstnumeric representation, and the corresponding line in the second numericrepresentation in said matching pair. By calculating the rotation anglesfor all matching pairs, a plurality of rotation angles is created. In asixth step, the frequency of all rotation angles+/− an alloweddifference may be counted, and the most frequent rotation angle may befound and be compared to the frequency values of the remaining rotationangles. If the minimum frequency difference is below a threshold value,the fingerprints do not match. In a seventh step, for each feature pointparticipating in each numeric representations in said plurality ofmatching numeric representations, the presence of the said feature pointin the remaining numeric representations in said plurality of matchingnumeric representations, is tested. A plurality of matching featurepoints, PMF, is created, where PMF comprises all feature pointsparticipating in all numeric representations where said feature point isfound. The number of matching feature points equals the number of uniquefeature points in PMF.

FIG. 4A shows an illustrative example of a table 400, which listssimilar values derived from the properties with the assigned numbers 52,49, 53. Upon reviewing the table 400 shown in FIG. 4A, it should beunderstood that only one binary search is required, and a number oflinear searches are enough to find all similar properties in the table400. If the numbers A, B, C in the table 400 represents the sides of atriangle, a person skilled in the art realizes that similar shapedtriangles will be found in the vicinity of each other. However, theinterleaving of digits does not always result in a list of consecutivevalues. FIG. 4B shows, in a table 450, another list of properties where2 binary searches are required to find the values concluded from similartriplets. More lists of properties can be created showing that more than2 binary searches may be required. It has been found that, if the usedbinary digits of assigned number of each property varies +/−1, thenumber of binary searches required to find all similar shaped propertiesin the sorted global table may be reduced significantly compared toprior art solutions. This should be realized upon reviewing FIG. 4A andFIG. 4B, and comparing this to a SQL statement which may be used inprior art solutions. Such a SQL statement may have the following syntax:

SELECT* From GLOBALTABLE where A>ACONST−2 AND A<ACONST+2 AND B>BCONST−2AND B<BCONST+2 AND C>CCONST−2 AND C<CCONST+2

Apparatus

In an embodiment according to FIG. 5, an apparatus 50 for searching adatabase comprising data related to a plurality of fingerprints,comprises:

an identification unit 501 adapted to identify at least two featurepoints in an image of an unknown fingerprint;

a first generation unit 502 adapted to generate a plurality ofproperties based on the at least two feature points;

an assignment unit 503 adapted to assign a number comprising a pluralityof digits to each of the plurality of properties;

a second generation unit 504 adapted to generate a numericrepresentation of said fingerprint based on the assigned numbers; and

a search unit 505 adapted to use the numeric representation as a searchargument when searching the database.

The second generation unit 504 is adapted to generate said numericrepresentation by at least partly interleaving said plurality of digits.

The unit(s) of the apparatus 50 may e.g. be in hardware, such as e.g. aprocessor with a memory. The processor could be any of variety ofprocessors, such as Intel or AMD processors, CPUs, microprocessors,Programmable Intelligent Computer (PIC) microcontrollers, Digital SignalProcessors (DSP), etc. However, the scope of the invention is notlimited to these specific processors. The memory may be any memorycapable of storing information, such as Random Access Memories (RAM)such as, Double Density RAM (DDR, DDR2), Single Density RAM (SDRAM),Static RAM (SRAM), Dynamic RAM (DRAM), Video RAM (VRAM), etc. The memorymay also be a FLASH memory such as a USB, Compact Flash, SmartMedia, MMCmemory, MemoryStick, SD Card, MiniSD, MicroSD, xD Card, TransFlash, andMicroDrive memory etc. However, the scope of the invention is notlimited to these specific memories.

According to another embodiment, the apparatus 50 comprises unit(s)adapted to perform the method steps defined in any one of theembodiments.

In an embodiment, the apparatus 50 is used in a police control or in acrime scene investigation.

In another embodiment, the apparatus 50 is used in a passage system atan airport, industrial park or building, etc.

In still another embodiment, the apparatus 50 is used for authenticatinga person to use a certain type of equipment. Examples of such equipmentare automatic cash dispensers, access systems, systems of various typesof electronic equipment, e.g. mobile telephones or computers.

Computer Program Product

In an embodiment according to FIG. 6, a computer program product 60 forsearching a database comprising data related to a plurality offingerprints, comprises:

an identification code segment 601 adapted to identify at least twofeature points in an image of an unknown fingerprint;

a first generation code segment 602 adapted to generate a plurality ofproperties based on the at least two feature points;

an assignment code segment 603 adapted to assign a number comprising aplurality of digits to each of the plurality of properties;

a second generation code segment 604 adapted to generate a numericrepresentation of said fingerprint based on the assigned numbers; and

a search code segment 605 adapted to use the numeric representation as asearch argument when searching the database.

The second generation code segment 604 is adapted to generate saidnumeric representation by at least partly interleaving said plurality ofdigits. The computer program product may e.g. be embodied on a recordmedium, stored in a computer memory, embodied in a read-only memory, orcarried on an electrical carrier signal.

According to another embodiment, the computer program product 60 forprocessing by a computer system comprises computer program code meansfor performing the method steps defined in any one of the embodiments.

The computer program product 60 may be loaded and run in a system havingcomputer capabilities. Computer program, software program, programproduct, or software, in the present context mean any expression, in anyprogramming language, code or notation, of a set of instructionsintended to cause a system having a processing capability to perform aparticular function directly or after conversion to another language,code or notation.

Some embodiments of the invention allow for improved speed of the searchprocess when searching a database comprising data related to a pluralityof fingerprints. It is an advantage of some embodiments of the inventionthat they allow for searching a database comprising data related to aplurality of fingerprints to find a match with improved performance.

The invention can be implemented in any suitable form includinghardware, software, firmware or any combination of these. However, itmay be advantageous to implement the invention as computer softwarerunning on one or more data processors and/or digital signal processors.The elements and components of the embodiments of the invention may bephysically, functionally and logically implemented in any suitable way.Indeed, the functionality may be implemented in a single unit, in aplurality of units or as part of other functional units. As such,embodiments of the invention may be implemented in a single unit, or maybe physically and functionally distributed between different units andprocessors. With reference to FIG. 5, the units 501, 502, 503, 504, 505can, e.g., be implemented in one or more computers connected in a localor remote network. Examples of such networks include, but are notlimited to, LAN, WAN, UMA, GAN, Bluetooth, etc. As an illustrativeexample, when using embodiments of the present invention in a policecontrol application it may be advantageous to have unit 501 in localdevice, whereas at least unit 505 is implemented in a remote server.

Combinations and modifications of the above-mentioned embodiments shouldbe able to be implemented by a person ordinary skilled in the art towhich this invention belongs.

Applications and use of the above-described embodiments according to theinvention are various and include all fields wherein fingerprintmatching is used.

Unless otherwise defined, all terms (including technical and scientificterms) used herein have the same meaning as commonly understood by oneof ordinary skill in the art to which the present invention belongs. Itwill be further understood that terms, such as those defined in commonlyused dictionaries, should be interpreted as having a meaning that isconsistent with their meaning in the context of the relevant art andwill not be interpreted in an idealized or overly formal sense unlessexpressly so defined herein.

It should also be emphasized that the singular forms “a”, “an” and “the”as used herein are intended to comprise the plural forms as well, unlessexpressly stated otherwise. It will be further understood that the terms“includes/including” and/or “comprises/comprising” when used in thisspecification, is taken to specify the presence of stated features,integers, steps, operations, elements, and/or components, but do notpreclude the presence or addition of one or more other features,integers, steps, operations, elements, components, and/or groupsthereof.

The present invention has been described above with reference tospecific embodiments. However, other embodiments than the abovedescribed are equally possible within the scope of the invention.Different method steps than those described above, performing the methodby hardware or software or a combination of hardware and software, maybe provided within the scope of the invention. The different featuresand steps of the invention may be combined in other combinations thanthose described. The different embodiments described above do not limitthe scope of the invention, but the scope of the invention is onlylimited by the appended patent claims.

The invention claimed is:
 1. A method for searching a databasecomprising data related to a plurality of fingerprints, the methodcomprising: identifying at least two minutiae points in an image of anunknown fingerprint; generating a plurality of properties wherein eachproperty of the plurality of properties is based on a relation betweenthe at least two minutiae points; assigning a number comprising aplurality of digits to each of the plurality of properties, wherein theassigning comprises assigning a number comprising a plurality of bits toeach of the plurality of properties; grouping the plurality ofproperties into a plurality of subsets of properties; generating aplurality of numeric representations of the unknown fingerprint based onthe plurality of subsets of properties; using the plurality of numericrepresentations as search arguments when searching the database; whereineach of the plurality of numeric representations is generated by atleast partly interleaving the plurality of digits; and wherein theassigning comprises assigning a respective binary number a₃ a₂ a₁ a₀, b₃b₂ b₁ b₀, c₃ c₂ c₁ c₀, d₃ d₂ d₁ d₀ . . . N₃ N₂ N₁ N₀ to each of theplurality of properties, and the generating comprises generating thenumeric representation by arranging the plurality of bits in thefollowing order: N₃ . . . d₃ c₃ b₃ a₃ N₂ . . . d₂ c₂ b₂ a₂ N₁ . . . d₁c₁ b₁ a₁ N₀ . . . d₀ c₀ b₀ a₀.
 2. The method according to claim 1,wherein interleaving comprises interleaving the plurality of digits suchthat the plurality of digits of the numeric representation are arrangedin an interleaved or intertwined manner.
 3. The method according toclaim 1, wherein interleaving comprises interleaving most significantbits of the plurality of bits.
 4. The method according to claim 1,wherein interleaving comprises interleaving all bits of the plurality ofbits.
 5. The method according to claim 1, wherein interleaving comprisesinterleaving the plurality of bits bitwise.
 6. The method according toclaim 1, wherein interleaving comprises arranging the plurality of bitsin order of significance, from most significant bits to leastsignificant bits within a numeric representation.
 7. The methodaccording to claim 1, further comprising: masking away at least someleast significant bits of the plurality of bits.
 8. The method accordingto claim 1, wherein the method is used for at least one of a crime sceneinvestigation, a police control, an authentication equipment or apassage system at an airport, industrial park or building.
 9. A methodfor searching a database comprising data related to a plurality offingerprints, the method comprising: identifying at least two minutiaepoints in an image of an unknown fingerprint; generating a plurality ofproperties wherein each property of the plurality of properties is basedon a relation between the at least two minutiae points; assigning anumber comprising a plurality of digits to each of the plurality ofproperties, wherein the assigning comprises assigning a numbercomprising a plurality of bits to each of the plurality of properties;grouping the plurality of properties into a plurality of subsets ofproperties; generating a plurality of numeric representations of theunknown fingerprint based on the plurality of subsets of properties;using the plurality of numeric representations as search arguments whensearching the database; and wherein each of the plurality of numericrepresentations is generated by at least partly interleaving theplurality of digits; and wherein assigning comprises assigning arespective binary number a₃ a₂ a₁ a₀, b₃ b₂ b₁ b₀, c₃ c₂ c₁ c₀, d₃ d₂ d₁d₀ . . . N₃ N₂ N₁ N₀ to each of the plurality of properties, andgenerating comprises generating the numeric representation by arrangingthe plurality of bits in the following order: a₃ b₃ c₃ d₁ . . . N₃ a₂ b₂c₂ d₂ . . . N₂ a₁ b₁ c₁ d₁ . . . N₁ a₀ b₀ c₀ d₀ . . . N₀.
 10. A methodfor searching a database comprising data related to a plurality offingerprints, the method comprising: identifying at least two minutiaepoints in an image of an unknown fingerprint; generating a plurality ofproperties wherein each property of the plurality of properties is basedon a relation between the at least two minutiae points; assigning anumber comprising a plurality of digits to each of the plurality ofproperties, wherein the assigning comprises assigning a numbercomprising a plurality of bits to each of the plurality of properties;grouping the plurality of properties into a plurality of subsets ofproperties; generating a plurality of numeric representations of theunknown fingerprint based on the plurality of subsets of properties;using the plurality of numeric representations as search arguments whensearching the database; and wherein each of the plurality of numericrepresentations is generated by at least partly interleaving theplurality of digits; and wherein assigning comprises assigning arespective binary number a₇ a₆ a₅ a₄ a₃ a₂ a₁ a₀, b₇ b₆ b₅ b₄ b₃ b₂ b₁b₀, c₇ c₆ c₅ c₄ c₃ c₂ c₁ c₀, d₇ d₆ d₅ d₄ d₃ d₂ d₁ d₀ . . . N₇ N₆ N₅ N₄N₃ N₂ N₁ N₀ to each of the plurality of properties, and generatingcomprises generating the numeric representation by arranging theplurality of bits in the following order: N₇ . . . d₇ c₇ b₇ a₇ N₆ . . .d₆ c₆ b₆ a₆ N₅ . . . d₅ c₅ b₅ a₅ N₄ . . . d₄ c₄ b₄ a₄ N₃ . . . d₃ c₃ b₃a₃ N₂ . . . d₂ c₂ b₂ a₂ N₁ . . . d₁ c₁ b₁ a₁ N₀ . . . d₀ c₀ b₀ a₀.
 11. Amethod for searching a database comprising data related to a pluralityof fingerprints, the method comprising: identifying at least twominutiae points in an image of an unknown fingerprint; generating aplurality of properties wherein each property of the plurality ofproperties is based on a relation between the at least two minutiaepoints; assigning a number comprising a plurality of digits to each ofthe plurality of properties, wherein the assigning comprises assigning anumber comprising a plurality of bits to each of the plurality ofproperties; grouping the plurality of properties into a plurality ofsubsets of properties; generating a plurality of numeric representationsof the unknown fingerprint based on the plurality of subsets ofproperties; using the plurality of numeric representations as searcharguments when searching the database; and wherein each of the pluralityof numeric representations is generated by at least partly interleavingthe plurality of digits; and wherein assigning comprises assigning arespective binary number a₇ a₆ a₅ a₄ a₃ a₂ a₁ a₀, b₇ b₆ b₅ b₄ b₃ b₂ b₁b₀, c₇ c₆ c₅ c₄ c₃ c₂ c₁ c_(o), d₇ d₆ d₅ d₄ d₃ d₂ d₁ d₀ . . . N₇ N₆ N₅N₄ N₃ N₂ N₁ N₀ to each of the plurality of properties, and generatingcomprises generating the numeric representation by arranging theplurality of bits in the following order: a₇ b₇ c₇ d₇ . . . N₇ a₆ b₆ c₆d₆ . . . N₆ a₅ b₅ c₅ d₅ . . . N₅ a₄ b₄ c₄ d₄ . . . N₄ a₃ b₃ c₃ d₃ . . .N₃ a₂ b₂ c₂ d₂ . . . N₂ a₁ b₁ c₁ d₁ . . . N₁ a₀ b₀ c₀ d₀ . . . N₀.
 12. Amethod for searching a database comprising data related to a pluralityof fingerprints, the method comprising: identifying at least twominutiae points in an image of an unknown fingerprint; generating aplurality of properties wherein each property of the plurality ofproperties is based on a relation between the at least two minutiaepoints; assigning a number comprising a plurality of digits to each ofthe plurality of properties, wherein the assigning comprises assigning anumber comprising a plurality of bits to each of the plurality ofproperties; grouping the plurality of properties into a plurality ofsubsets of properties; generating a plurality of numeric representationsof the unknown fingerprint based on the plurality of subsets ofproperties; using the plurality of numeric representations as searcharguments when searching the database; and wherein each of the pluralityof numeric representations is generated by at least partly interleavingthe plurality of digits; and wherein assigning comprises assigning arespective binary number a₇ a₆ a₅ a₄ a₃ a₂ a₁ a₀, b₇ b₆ b₅ b₄ b₃ b₂ b₁b₀, c₇ c₆ c₅ c₄ c₃ c₂ c₁ c₀, d₇ d₆ d₅ d₄ d₃ d₂ d₁ d₀ . . . N₇ N₆ N₅ N₄N₃ N₂ N₁ N₀ to each of the plurality of properties, and generatingcomprises generating the numeric representation by arranging theplurality of bits in the following order: a₇ a₆ a₅ a₄ a₃ a₂ a_(l) a_(o)a₇ b₇ c₇ d₇ . . . N₇ b₆ c₆ d₆ . . . N₆ b₅ c₅ d₅ . . . N₅ b₄ c₄ d₄ . . .N₄ b₃ c₃ d₃ . . . N₃ b₂ c₂ d₂ . . . N₂ b₁ c₁ d₁ . . . N₁ b₀ c₀ d₀ . . .N₀.